PSY201H1 Lecture Notes - Lecture 8: Construct Validity, Covariance, Experiment
Document Summary
The problem with hypothesis testing with z-scores is that the z-score formula requires that we know the value of the population standard deviation (or variance) But in most situations, we don"t have this type of information. We use our sample variance as an estimate of our population variance (sample variance is an unbiased estimate of the population variance because we use the degrees of freedom rule (n-1)) If we don"t know the proper standard error (for the population) we"ll use an estimated standard error (from the sample) The t-statistic is used to test hypotheses about an unknown population mean when the value of. The ratio between the observed difference we actually have, and how much difference we"d expect by chance. The formula for the t statistic has the same structure as the z-score formula, except that t- statistic uses the estimated standard error in the formula. The large the sample (n) is the better he sample represents its population.
